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  <doi_batch_id>aspg-40-3834-1792469439</doi_batch_id>
  <timestamp>20261020041039</timestamp>
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  <journal>
   <journal_metadata language="en">
    <full_title>Pure Mathematics for Theoretical Computer Science</full_title>
    <abbrev_title>PMTCS</abbrev_title>
    <issn media_type="electronic">2995-3162</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2025</year>
    </publication_date>
    <journal_volume>
     <volume>5</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Neighborhood HyperRough Set and Neighborhood SuperHyperRough Set</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Takaaki</given_name>
      <surname>Fujita</surname>
      <affiliations>
       <institution>
        <institution_name>Independent Researcher, Shinjuku, Shinjuku-ku, Tokyo, Japan</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Fuzzy sets,20 rough sets,14 intuitionistic fuzzy sets,3 neutrosophic sets,15 soft sets,13 hesitant fuzzy set,17 plithogenic sets,16 and other uncertainty-handling frameworks have been the focus of intensive and ongoing research. Rough set theory provides a mathematical framework for approximating subsets through lower and upper approximations defined by equivalence relations, effectively capturing uncertainty in classification and data analysis.5, 10 Building upon these foundational concepts, further generalizations such as Hyperrough Sets8 and Superhyperrough Sets have been introduced. In this paper, we investigate the concepts of Neighborhood Hyperrough Sets and Neighborhood Superhyperrough Sets. These models extend the classical Neighborhood Rough Set framework by incorporating the structural richness of Hyperrough Sets and Superhyperrough Sets.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2025</year>
    </publication_date>
    <pages>
     <first_page>23</first_page>
     <last_page>29</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">3834</item_number>
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     <doi>10.54216/PMTCS.050104</doi>
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